Utilizing Variational Autoencoders in the Bayesian Inverse Problem of Photoacoustic Tomography-Reference-Cited by-同舟云学术

Utilizing Variational Autoencoders in the Bayesian Inverse Problem of Photoacoustic Tomography

Published:2023-01-24 Issue:1 Volume:16 Page:89-110
ISSN:1936-4954
Container-title:SIAM Journal on Imaging Sciences
language:en
Short-container-title:SIAM J. Imaging Sci.

Author:

Sahlström Teemu¹^ORCID,Tarvainen Tanja²

Affiliation:

1. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.

2. Department of Applied Physics, University of Eastern Finland, Kuopio, Finland, and Department of Computer Science, University College London, London, United Kingdom.

Funder

Academy of Finland

H2020 European Research Council

Jane and Aatos Erkko Foundation

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,General Mathematics

Reference44 articles.

1. Uniqueness of reconstruction and an inversion procedure for thermoacoustic and photoacoustic tomography with variable sound speed

2. Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning

3. Deep learning for photoacoustic tomography from sparse data

4. Accelerated high-resolution photoacoustic tomography via compressed sensing

5. Biomedical photoacoustic imaging

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Diffusion assisted image reconstruction in optoacoustic tomography;Optics and Lasers in Engineering;2024-07

2. A dimension-reduced variational approach for solving physics-based inverse problems using generative adversarial network priors and normalizing flows;Computer Methods in Applied Mechanics and Engineering;2024-02

3. Quantitative photoacoustic tomography: modeling and inverse problems;Journal of Biomedical Optics;2023-12-20